From:NPR

The argument that the tariffs are about negotiations fits an image Trump likes to present — that he’s a master dealmaker, NPR’s Danielle Kurtzleben tells Up First. Trump said he’s spoken to multiple world leaders, including from Japan, South Korea and Vietnam. There has been some back and forth between the U.S. and China over retaliation, which has resulted in tariffs for goods from that country now being at least 104%. 

(Take a look around your home-especially your closets-where are most of your items made?)

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Yesterday, in a brief unsigned order, the U.S. Supreme Court allowed the Trump administration to move forward with firing 16,000 probationary federal employees. The decision wasn’t a complete victory, as the court didn’t rule on whether the firings were lawful.

(Lawful? Is it me or are they just following Trump’s orders? This is no “supreme court”.)

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Nvidia CEO Jensen Huang attended a $1 million-a-head dinner at Mar-a-Lago last week, a chip known as the H20 may have been on his mind.

That’s because chip industry insiders widely expected the Trump administration to impose curbs on the H20, the most cutting-edge AI chip U.S. companies can legally sell to China, a crucial market to one of the world’s most valuable companies.

H20 had appeared as if it, too, would be subject to a Trump administration crack down. And tech companies in China responded. In the first three months of the year, leading Chinese tech firms purchased $16 billion worth of H20 chips, The Information reported last week, stockpiling the components in anticipation there would soon be U.S. export controls on the chip.

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What is H20?

Model Explainability

H2O Explainability Interface is a convenient wrapper to a number of explainabilty methods and visualizations in H2O. The main functions, h2o.explain() (global explanation) and h2o.explain_row() (local explanation) work for individual H2O models, as well a list of models or an H2O AutoML object. The h2o.explain() function generates a list of explanations – individual units of explanation such as a Partial Dependence plot or a Variable Importance plot. Most of the explanations are visual – these plots can also be created by individual utility functions outside the h2o.explain()function. The visualization engine used in the R interface is the ggplot2 package and in Python, we use matplotlib. Skip to the Explanation Plotting Functions section to examples of all the visual explanations.

You can read more at:https://www.npr.org/

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